Bibliographic record
Abstract
Drawing on ethnographic research with undergraduate students on their listening and sleeping practices, this essay develops a concept of “so(m)niferous media” to describe how listeners/sleepers use audio media to (re)mediate their experience of the night. The essay outlines key theoretical and practical affinities between sleeping and listening, taking a sociocultural approach to sleep informed by critical work in sound and media studies. Sleeping is reconceived as a sonically mediated, non-conscious experience of listening that participates ambivalently in the 24/7 logic of commodification outlined by Jonathan Crary and others. One unexpected finding of the ethnographic work is that many sleepers deliberately avoid obvious sound media products for sleeping (e.g., sleep playlists and podcasts, noise machines, “nature” sounds, binaural beats, etc) and seek out attention-grabbing social media content instead. Rather than lull themselves to sleep, listeners seem to want to engage their attention fully, while paradoxically shutting it down at the same time. So(m)niferous media thus seem to work directly on the attention of the listener, not the acoustic ambience of the sleeping space.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".